In recent decades, the development of computer-controlled manufacturing by adding materiallayer by layer, called Additive Manufacturing (AM), has developed at a rapid pace. The technologyadds possibilities to the manufacturing of geometries that are not possible, or at leastnot economically feasible, to manufacture by more conventional manufacturing methods. AMcomes with the idea that complexity is free, meaning that complex geometries are as expensiveto manufacture as simple geometries. This is partly true, but there remain several design rulesthat needs to be considered before manufacturing. The research field Design for Additive Manufacturing(DfAM) consists of research that aims to take advantage of the possibilities of AMwhile considering the limitations of the technique.

Computer Aided technologies (CAx) is the name of the usage of methods and software thataim to support a digital product development process. CAx includes software and methodsfor design, the evaluation of designs, manufacturing support, and other things. The commongoal with all CAx disciplines is to achieve better products at a lower cost and with a shorterdevelopment time.

The work presented in this thesis bridges DfAM with CAx with the aim of achieving designautomation for AM. The work reviews the current DfAM process and proposes a new integratedDfAM process that considers the functionality and manufacturing of components. Selectedparts of the proposed process are implemented in a case study in order to evaluate theproposed process. In addition, a tool that supports part of the design process is developed.

The proposed design process implements Multidisciplinary Design Optimization (MDO) witha parametric CAD model that is evaluated from functional and manufacturing perspectives. Inthe implementation, a structural component is designed using the MDO framework, which includesComputer Aided Engineering (CAE) models for structural evaluation, the calculation ofweight, and how much support material that needs to be added during manufacturing. Thecomponent is optimized for the reduction of weight and minimization of support material,while the stress levels in the component are constrained. The developed tool uses methodsfor high level Parametric CAD modelling to simplify the creation of parametric CAD modelsbased on Topology Optimization (TO) results.

The work concludes that the implementation of CAx technologies in the DfAM process enablesa more automated design process with less manual design iterations than traditional DfAM processes.It also discusses and presents directions for further research to achieve a fully automateddesign process for Additive Manufacturing.

Additive manufacturing (AM) is a group of manufacturing methods which have attracted rapidly increasing interest in academia and industry during the last years. AM's main benefits are manufacturing of complex shapes and small-scale manufacturing, without the additional cost of traditional manufacturing methods. Creating complex geometries that fully leverage the potential of AM requires time, knowledge, and design skills. Design for additive manufacturing (DfAM) is a vast area that includes methods and tools that aim to overcome the challenges of AM and support the development of new components and products.

Design automation and optimization are two terms often mentioned as potential methods to support the DfAM process. In a broad definition, design automation (DA) refers to reusable computer tools developed to aid the design engineering process. The general idea with DA is to create flexible design processes where different solutions can be explored without an increase in manual work. Together with methods for design optimization, DA has shown the potential to support the DfAM process.

This work focuses on how DA technologies can support the development of components manufactured by AM. By analyzing the current state of the art, today's DfAM process is mapped, and the potential for automation is explored. The work contributes to the field by presenting a holistic DA framework that bridges function, design, AM setup, and post-processing. A master model is used to span the different phases of the design process and utilize combined optimization of geometry and manufacturing setup. The proposed method is refined in an iterative process where details are solved, and computer tools supporting the process are developed. Application cases from the aerospace sector and the fluid power industry are used to evaluate and demonstrate the developed methods and computer support.